{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "% matplotlib inline\n",
    "\n",
    "import matplotlib.style\n",
    "import matplotlib.pyplot as plt\n",
    "plt.rcParams['figure.figsize'] = 12, 4\n",
    "matplotlib.style.use('ggplot')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "pd.set_option('display.max_rows', 8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pydetect"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x10e0300b8>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAtEAAAEDCAYAAADz11i+AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzsnXlgXGd19p8z2pcZ7ftiSba8REns2ImdGLKQmCxQIITg\n0EIpkEJL2g8CfJRCSROXQltoQ6AhSQMNgXwsTcKSBQoxcVYcx07iLZLj3dauGUkjzSJrvef7452R\nZqRZ7szcWXV+/yS+c+feV9LV6Nxzn/M8xMwMQRAEQRAEQRB0Y0r2AgRBEARBEAQh3ZAiWhAEQRAE\nQRAiRIpoQRAEQRAEQYgQKaIFQRAEQRAEIUKkiBYEQRAEQRCECJEiWhAEQRAEQRAiJFvPTrt27cJD\nDz2EBx54AMXFxQCAJ598Er29vbjtttswOzuLe++9F3a7HTU1NUG3CYIgCIIgCEImELYTferUKczM\nzKC9vX1+2+DgIF5//fX5fz///PNoaGjAjh07MDg4iL179wbcJgjpQmdnZ7KXIAghkWtUSHXkGhVS\nnViv0bBFdFtbG6677jq/bY888gg+/OEPz/+7q6sLW7ZsQVdXF9rb23Ho0CEcOXLEb9vhw4djWqgg\nJBL58BdSHblGhVRHrlEh1Yl7Eb2YnTt3YuPGjSgrK5vf5nQ6UVRUhN27d2Pbtm1wOBxLto2Pj8e0\nUKNJlV9uWYc/qbIOq9Wa7CWkzPdC1uFPqqxDrtEFZB3+pMo6UuEaBVLj+5EKawBkHYuJ9RqNuIh+\n/fXX8fLLL+Oee+7BwYMH8f3vfx8lJSV44oknsG3bNtjtdpSUlMBisfhtKy0tjWmhRpMqP0BZhz+p\nsg6bzZbsJaTM90LW4U+qrEOu0QVkHf6kyjpS4RoFUuP7kQprAGQdi4n1GiVmZj077tixA1/4whfm\nBwttNhsee+wx3Hbbbdi1axf27duHL33pS3jwwQexYcMGuFyuJds2b97sd8zOzk6/b+T27dtj+mIE\nQRAEQRAEQS+PPvro/P93dHSgo6ND93vDFtHd3d14/PHHceTIEbS3t2PLli248sor/YporxPHyMgI\n6urqgm7TQ39/v+7FC0K8MJvNcDqdyV6GIARFrlEh1ZFrVEh16uvrY3q/7k50opAiWkgF5MNfSHXk\nGhVSHblGhVQn1iJawlYEQRAEQRAEIUKkiBYEQRAEQRCECJEiOs4wM9gxluxlCIIgCIIgCAYiRXS8\nOd4F7e47kr0KQRAEQRAEwUCkiI4zfPItwDoA1rRkL0UQBEEQBEEwCCmi4wyfOgrMTAMOe7KXIgiC\nIAiCIBiEFNFxhJmB08eA0nLANpTs5QiCIAiCIAgGIUV0PLEPA9ocaPX5YNtgslcjCIIgCIIgGIQU\n0fHk1FGgbQ1QWQsMSydaEARBEAQhU5AiOo7w6WOg1tVAVQ0wLJ1oQRAEQRCETEGK6DjCp46C2taA\nqmrBookWBEEQBEHIGLKTvYBMhWdngZ7TQEs7MOGWTrQgCIIgCEIGIUV0vOg7C1RUgwoKwXl5gMsB\nnpkG5eQme2WCIAiCIAhCjIicI054pRwAQKYsoLwKGLYmeVWCIAiCIAiCEUgRHS9OHwVaVy/8u7JW\nJB2CIAiCIAgZghTRcYJPHQO1LRTRVFUjXtGCIAiCIAgZghTRcYDdLmB8FKhvXthYWSNe0YIgCIIg\nCBmCFNHx4PQxYMUqpYX2IDZ3giAIgiAImYMU0XFADRWu9t8ommhBEARBEISMQYroOKCSCtf4b6xS\ncg5mTs6iBEEQBEEQBMOQItpgmFnJOVr9O9FUWAyYTIDLmaSVCYIgCIIgCEYhRbTRWAeAvHxQafnS\n10TSIQiCIAiCkBFIEW0wfPooaFEXeh6xuRMEQRAEQcgIpIg2mlNHgcVDhR5IbO4EQRAEQRAyAimi\nDUaFrKwJ/GJlrRTRgiAIgiAIGYAU0QbC01PAQDfQvDLg68orWuQcgiAIgiAI6Y4U0UbSfQqoawbl\n5gV+vaoGkCJaEARBEAQh7ZEi2kCUP3SQoUIAKK8CxkfBs7OJW5SgG548B23fS9Ae/yH43ESylyMI\ngiAIQgqTnewFZBSnjgIXXBz0ZcrOASxlgH0YqKpN4MKEYPC5CfChfeDX/ggcPQSsXAcQYeIHd4P/\n4jMgomQvURAEQRCEFESKaAPh08dget+HQ+9UVaskHVJEJxU+chDas08Bx94E2jtAm7aCPvYZUFEx\neHoKc//2JfALvwNddUOylyoIgiAIQgoiRbRB8LgdODcB1NSH3I8qa8DDQ5D+ZvJgZmg//A7oXR8E\nfeJzoMIiv9cpNw+Ft98F5z/+Lbh1NWhF4EFRQRAEQRCWL6KJNorTyh867OP/yhpJLUw2PaeAnBzQ\nldcvKaC9ZNU3gf7sr6D917+BJ1wJXqAgCIIgCKmOFNEGwafCDBV6qaoFbOIVnUz4wF7Q+s1hb3hM\nl1wOOn8jtIe/C2ZO0OoEQRAEQUgHpIg2CD51FNQaJGTFB6qU6O9kw4f2gdZv1rUvffBWYHQY/OyT\ncV6VIAiCIAjphBTRRtF9CmhpD79fVQ0wIp3oZMGjwyo1cuU6XftTTg5Mf/V34N8+Dj75VpxXJwiC\nIAhCuiBFtAHwzDQwPQUUm8PvbC4FpqfBE+74L0xYAh/aB+rYCMrWP1NLVbUwffRvoD34LbDLEcfV\nCYIgCIKQLkgRbQRuJ1BUrMtTmIiULnpYutHJgA/tAzbok3L4QhsuBV38NvBP/ysOqxIEQRAEId3Q\n1Y7btWsXHnroITzwwANwuVx44IEHwMyYm5vDV7/6VWRnZ+Pee++F3W5HTU0NbrvtNszOzi7ZlrG4\nXUCRji60F69DR3Nb/NYkLIGnJoHjnaC//EJU76dt74P2tdsNXpUgCIIgCOlI2E70qVOnMDMzg/Z2\npfctKyvDV7/6VezYsQOrVq3CqVOn8Pzzz6OhoQE7duzA4OAg9u7dG3BbImFm8BuvJMZVweWMqIj2\nekULscMTbnDXAX07dx0AWlcHtbULS2k5MDsjkg5BEARBEMIX0W1tbbjuuuvm/52Xl4fs7GzMzMyg\np6cHbW1t6OrqwpYtW9DV1YX29nYcOnQIR44c8dt2+PDhuH4hS3A7od3/L+BXdiXgXA59emgvYnNn\nGLznOWjf+2ewwx5+34Ov6nblCAQRAbWNwGBv1McQBEEQBCEziFoT/fDDD+OWW25Bfn4+XC4XioqK\nsHv3bmzbtg0OhwNOp9Nv2/j4uJHrDs+IFSg2g3/5Y7A7vmEZ7HaBIupE14IlcMUQuOsAUFIO/t0v\nQ++nzYEPvQa68JKYzke1jeABKaIFQRAEYbkTVez3448/jo0bN2L1ahUuYjab8eSTT2Lbtm2w2+0o\nKSlBbm4unnjiifltpaWlS47T2dmJzs7O+X9v374dZnMEHd0QTE84Mb32QpjKKoDf/ByFt37OkOMG\nYnJmGlxWgQKda59raYN7xGbY17pc4dkZjB/rhPmu78D1T59D0U1/rn7eAZg91omJ0nJY2nTYEALI\nzc0N+POZbFkFHhnS/bMWhHgR7BoVhFRBrlEhHXj00Ufn/7+jowMdHR263xtxEd3b24ve3l7cfPPN\nfifdt28fWlpa8OCDD2LDhg1wuVxLti0m0GKdTmekSwqI1tsNlJRDe/eHoN35N5jdfCVIj49zNOca\ntQFFZszqXDvnF0OzDcIxPg4yiUFKtPDRN4HqOkyUVwOXXgXn4z+C6UOfDLiv9spzwAUX676+zGZz\nwH25vAra4dd1/6wFIV4Eu0YFIVWQa1RIdcxmM7Zv3x71+8NWcN3d3bj77rvR29uL++67D3v27MHJ\nkyexY8cO7NixA/v378cVV1yBvLw83HHHHZidncXmzZsDbksoI1agvApUVAy66aPQfvIAWJuLz7nc\nLqCoWPfulJen9h8bjc96lgnc+QaoYyMAgK7/APiV58BjI4H3PbgvZikHAKCuCRjoif04giAIgiCk\nNWE70c3Nzfj85z/vt823C+3l9tv9rb+ys7OXbEskPGKFabXqctNlV4Nf2gl+aSfoyuuNP5fLCVOR\nJbI3eW3uyisNX89ygTv3w3TLrQAAKi0Hve0a8P/+AvSnn/LfzzYIuBxA6+rYT1pZAzjGwFNT6mZI\nEARBEIRlSeZqCYatQEU1AOWqYPrwX4Of+AnYGYcBxwlnZO4cUCl46Wxzx1OT0H58b/LO7xwHbANA\n29r5bXT9TeBXX1DR3r77HtwLuuBiQ6QzlJWl3FWG+mI+liAIgiAI6UvmFtGjC0U0AFBjC2jLVeBf\n/Mj4c7mcEck5AKiOZjrb3A32gnc/mxgf7gBw1wFg9fl+8d1kKQO9bRv4fx/33/fgXlAUKYVBqWsE\ni6RDEARBEJY1GVlE84QbmJtbEoBC7/1TcOd+8IkuY0/odgIRyzlqlZwjTWHrgPoen3MnZwGd++f1\n0L7Qde8H730RPGoDAPCECzhzHFi3dLA1WqiuSbyiBUEQBCEIPG4H79+T7GXEnYwsor1daCLy20wF\nhaAPflwNGc4ZM2TIzJ4iOrJONFXVKK1uumIdUP9NQnofM4O7DoA6lhbGZCkFXXEd+LePqX3ffANo\n7wDl5Ru3gFrpRAuCIAhCMPitQ9AWPRXORKLyiU40PDYCZOeAinV2e0dsflIOX+iSy8EvPQN+/GFg\n5ZrA71+5DhTEb3gJU5OAyQTKjXDIrLJG6bbTFe8NgNMBVNcn9tx9Z4HcXFCQ89K174d2x6fBN9wM\nGC3lgOpEe4t0QRAEQRAWMToMeJ4IZzIpX0TzhBvaN78MuuQK0Ps/ou89w1ZQRVXA14gIpj+/Dfzr\nn0B77eWlOwwNgM5bD/rgJ/Qt0O2KXMoBAKXlgNuZti4PbBsE8vKT04nu3A86L7g8g8wW1Y1+6mfg\nN9+A6YMfN3YBNQ2AbRA8N6cGDQVBEARBWMBuA8bt4JkZUE5OslcTN1K6iGZmaD/6TyArCxyJBnXR\nUOFiqLoe9KkvBnxN2/0scOSQ/nO5HZEPFQIgU5Za48gQUN8c8fuTjnUAWLEK7HKAwu9tKNy1H6ar\n3hVyH7r2Rmhf/iRQ0wAq1flUQSeUlwdYSoHhIaAmwV14QRAEQUhx2O7JbLAPA9V1yV1MHElpTTTv\nehoYscL08dsjGuTi4dBFdCjIXAp2jOl/g8u5ZIBRN1Xp6dDB01OAywFqbgPiYRkY6txTU8DJo8Da\nC0PuR8UW0Ps+DLri2vgsREJXBEEQBCEwo8NAXkHGSzpSthPNp46Cf/MoTF/+FmApU4/PtTnVwQ3H\niBUUZRENSyng1F9Es9sVsUe0F6qsAQ8PJbyTGzPDQ+omxVKWeDnH8U6gqRVUUBh2V9O298ZtGVTX\nCB7oBW3YErdzCIIgCEJaYh8G2laDR2zpV+NEQEp2otnthPbgt2D6878BVdWqx+fmEjUwqIfR4IOF\nYTGXRNZddTtAUXeiawFrf3TvTSa2QbX2YrMaLDQI7ScPgI8eDrkPd+4HdVxk2DmjRjrRgiAIgrAE\nnpkGzrlBLe0Z34lOuSKaNQ3aQ/eANl4GuujShRdqG3RJOnhqEpg8p4rhaDCXAE4HWNP07e92RS3n\noKY2cPfJqN6bTNg6oG5uzBawQZ1oZgbveQ7a9/8DPG4Pvl/nGylRRFNdY2Q6fUEQBEFYDtiHgZJy\noLJaiuhEw8/8CnA7QTf9hd92qm0ED+qIWh61AeVVUUc8U04OkJenP0QkFk30ilVAz2nDPKsThm1A\nDQoUlxgn57APA7l5oMuvhfb9fwdrS78nPDoMOMaAFSuNOWcs1Daq1MYkJTYKgiAIQkoyOgyUV4LK\nq+aDzzKV1Cuidz4B06e+6BfnDEB3JxrDViCIvZ1uzKWqWNOD2xG9JrqwCCirAPq7o3p/smDbIKiq\nDii2GDdY2N8D1DeD3nMLQAR+6udLz9u1H7RuvT5dfJyhYguQnQOMjyZ7KYIgCIKQMrB9BFRWpWS1\nUkQnFtPHPgsqX1oEU02Drk40xzJU6MVcAjj0FYfsdkWviQZALavBZ45H/f6kYB0EqmvV98nlNOSQ\n3N8Nqm8GmbJg+uQXwC/vVGmDvnQdAFJAyjFPXSMwIJIOQcFvHVLONYIgCMuZURtQXgmUVQKjtox+\nYptyRTRdsCnwC7WNwJAeOUf09nbzROLQ4Y5BzgEALe3A6WPRvz/B8Nyc+h5X1gAFhcD0JHh2NvYD\n93erYT0AZCmD6S+/AO2H9ygJBwDW5sBHDoDOS50immqbJP5bAODxtP/ODmg7Pgs+3pXs5QiCICQP\n+zBQVgHKLwBy8gxrtqUiKVdEB6WsApg8B54Io1WOwSPaC1lK9HtFu51RyzkAgFrbDe1Es9tl2LEC\nMmoDLKWgnFylOy8sNkQXzQM9IJ/QGVpzAejqP4H2/W+pIv3sKcBcCiqvjPlchiGdaMHL9BRgIpg+\n8BfQHvwmtJ9/Xw05C4IgLDN4dHjhb3V5ZUZLOtKmiCYiFbccphvNozYD5Byl+rW+LmdUiYXzNLUC\nQ30qRCRGeKAH2j/ept9ZJBpsg0CVT/qQOfbhQmZWdnH1TX7b6YabgfwC8K8f8bhybIzpPEZDdU3i\n0CEo3E6g0AzaeBlMd/0n4HZB2/GZsJaNgiAIGYd9GCjzyHLLq6SIThWoVocu2ojBQos+TTRrGjDh\nAgpj6ETn5AJ1zUDPqaiPMb+e7lNqILL3TMzHCnoO2yCoqnZhQ7El9k60fRjIyVXDej6QyQTTJz4P\n3vcS+Pnfgjo2xHYeo5FOtODFtfBEiorMMN36OZhu+SS0//42tJ/cD56cSPICBUEQEoTHnQNAxjt0\npFURjZrQDh08M6PcMkrLYzqN7ujvyQkgL3+pk0ik52tZBT5jgC667yyQlQV+62DsxwqGdUAFrXgp\ntoBjDVzxOHMEgswWmD75RYAIaD8/tvMYTVklMDkRVmKkPfRt8LE3E7QoISkEmI2g9ZfAdNd3galJ\naP/5z0lamCAIQuLgqUlgZlo12ADV1JQiOkWoC+MVbbcBpRWxW6DpHSx0OZUmOFZaVwOnT8R8GO7v\nBm16G/it+D1CZtsAqHpBzkHm2DvR3N8NqmsK+jqtWgfTvz2kkitTCCJSA68hhgt5qB/8ynPgfhlA\nzGiCDBhTYTFo+61Az+kkLEoQBCHBeIcKyRP2XV6lP206DUmrIprCdKKNGCoEoD/62+1cuNuKAWpp\nN6wTTVf/CXCiyxjHjEAs1kQb4RU9ELwT7SXa8Jx4Ey65kHc9DeQVAI7gKYxC+sNuFyjYgHGRGZib\nEUmHIAiZz+iwekrrQeQcqURNA2AbDJhmBxjkEQ14NNE6OtHuGIcKvdQ1AuNjYHf0NjA8OaHW3Nqu\n7OeMKMoXn4PZU0Qbq4n2ekSnJSE60TzhBu95HnT1u4FxnW4vQnricgT9LCAiNWTjsWsUBEHIVNg+\nDPIpotVgYeZ+9qVVEU15eapLHOzRwIgBQ4UAUFAEzM6EDU5glzOmoBUvZMoCVrQBZ2KQdPT3ALWN\nIFMWaN168JFDMa9rCY4xNQBYWLSwLUZ3jmDOHOmCcugILDHi3c+COi4CtazSb5kopCduJ1AU4qlU\neWVG/yERBEEA4DdUCAAoKQXcDjWzloGkVRENIHT894gNqKiJ+RRE5LG5C1Mcul0xeUT7nTPG5ELu\nOwtqWKGOtXZ9fIYLbYuGCqHirzmWTrR9JKAzR9pQ1xSwE83aHHjX06Br3gNYykTOkem4XSGfSlFZ\nJdguRbQgCBmOfZGcw5QFlJSr7RlI2hXRVBt8uJBHhkBGdKIBNVwYrnvodsSWVugDtbaDY0ku7DsL\neIpotJ8HnD1peNgDWwdBvnpoADBbwt9shKK/O6weOqWpqgVGh8Ez0/7bD7+uro22NepaGpciOpNh\ntzO4JhqQTrQgCMsCHrUtDUXLYIeOtCuiw3eiDdBEA57hwjBFtCvGyG9fWtqBM8ejzpjn/m5QgypG\nKb8AaGoDjI4ftg0C1f6d6Fg10eGcOVIdys5WGvShfr/t2rNPga55j3qq4bkhi/ZnK6QBnrCVoJRV\nZmwnRhAEYR77iL+cA5k9XJh2RTTVBA5c4bk59ci8zJhYaDKXgMO5TrhdxhXRFdWApqkLMBp6zwAN\nLfP/pHUXGi/psA74O3MAniJ6PPoCUYczR8pT1wj2CV3hvrNAfw/o4rcB8NzUmLKAc+LOkLH4hK0E\ngspFziEIwjLAN63QSwanFqZdEY3axsDR3/ZhwFIac/DJPDrkHOx2hH6EGwFENN+NjhR2jAFzs34h\nM7TW+OFC5RG9SBOdmwdkZQNT56I7Zn83KE2HCr1QXZPf0xF+9inQldeDsnMWdirRIQ8S0hd36CJa\n3DkEQch0+NwEMDcH+JoPABnt0JF+RXRZBTB5bmlK3IgNKDdIygHoi/42shONGPyi+7uB+hUL5uYA\n0LYasPbHZJu3hMUe0V6Ko9NFLzhzpH8n2jtcyC4H+PU/gq68zn8fGS7MWJgZmHCFDl4qqwDswyLp\nEQQhc/E4c/jVIgCoogqcoYEraVdEE5Hyi17UjTZ0qBBQ7hxhBwsN1ETDM1wYhc2dcubwL0QpOwdY\ntQ44akx6IU+4VZSnpXTpi9HqotPdmcMD1TXNyzn4pZ2g9VtAljL/nSylYPGKDgkf2gftyZ8lexmR\nM3lOXce+Tx4WQYVFKro+TES8IAjpi/bje5d3qJLdFlhSK3KO1IJqA+iiDbK3mz+HpRSsZ7DQIDkH\nAI+c4wRY0yJ7X99ZPz20F1p7oXGSDk/IyuI7TADKoSOaIrq/W1nEpTs1DYC1Dzw7A37+N6Bt71my\nC5WUSic6BHxgD7SHvwv+wxOxWSYmA5dOl56ySvVHRhCEjIOnJsEvPQOcPJrspSQNHh1e6swBeNyJ\nbBn5JC4ti2gEiv82KmjFS5job56bUx2ogkLDTknmEqUlsvaH39l3LT7OHH7HM9IvOoBH9Px5ii3g\naOQcAz3pm1ToA+UXAMUW8B+eBCqqQc0rl+5kKRObuyDwG69A+/H3YPrsnaDzN4H3vZTsJUWG3idS\nYnMXNcwM7aVnkr0MwQAy9mdpHQAA8IkjSV5IEgk0VAiA8guB7Bz1WZlhpGcRXbfUK5pHrKBKozXR\nITrREy6gsEgZiRsIta4Gn9Y/XMjM/h7RvjS1Ak4HOFrHD9/z2AJ4RHvxOHRETLp7RPtS2wR++n9g\numZpFxoAUFImg4UB4Nd3Q/vJ/TDdfhdoxSrQ1mvAf3w22cuKjDBBK16UzZMU0VHhcoB/fK8aXBLS\nm7FR9bPMtILKOgDkF4BPLvMiOlAnGshYSUdaFtEUrBNt5GBhcQngdgaXVhish54nUoeOURuQXxAw\nfpxMJmDNBeAjBnSjbYNAdagiOtpOdAbIOQBQXaO6HjZcGvh1S6lEfy+CX3sZ2k8fgOmzdy10789b\nD4yPgvu6k7u4CGCXQ5+uX7yio2fYqv47FntDQEgyI0Pqv2n0O64HtvaDNm0FTh9TT6qXITw6DCqr\nCPxihgaupGURjZoGwDYI1tSFypqm/jgZKOeg7Gwgv1B1mQLhcurqPkV83kiTC/vOAvUButDe4627\nEDBA0sHWAVAQOUc0qYXMnFGdaNq4Fabtt4KygjyZEDmHH9q+l6D9/Psw3b4D1Nw2v51MWaBL3wF+\nJY260RP6OtEi54gBb+ElNyFpD3tuiLg/s4poWAeA1jVAaQXQdybZq0kOQeQcgMcrfyTzfn/Tsoim\nvDylWfZapozbgSIzKCfX2BOF8op2O1UH1miaVwJ9Z8GzM7p2D+TM4YvXLzqUoJ+1ufCC/5Ca6JLI\nh8HsI0B2Tto7c3ih1R2qCxEMGSycR3v1BfD//EAV0E2tS16nrVeD9zyfPt0cncmlVCaBK9Hitcdi\n+2iSVyLEzPAQkF8A9J9N9koMha39oOo60Kp1aamLZm0uclMD3/czz1vcBWQ5yzl27dqFj3zkI3C5\nXJidncU999yDO++8E/fddx8A6N5mKL7x3yNW9QMymhDR3+x2guLRic4vUMVqn84PmCDOHPPU1Ctr\nrUABNVAdZu3OvwX/9rGgh+CZGeWZHex7HI2cIxP8oSPBXAo4x2P6kMoEeHIC/Mj3YPrcP4EaWwLu\nQ3VN6lrr2p/YxUVLuKAVL54JdSEKRjyFl9yEpD8jVuC8i8D9PcleibEMDQDV9cpaNh2L6Md+CH72\nqegPMOECsrJAwcwWlmsRferUKczMzKC9vR0A8Pzzz6OhoQE7duzA4OAg9u7dq3ubkVDtwnChGio0\nzt5u/hyhor91dp+iOm/LKt3DhdwX2Jlj/lhEyururaVWd3ziCLRv/j1o09vAf3gSPBFEujI8BJRX\nBZcqRCPn6O/OCGcOvVBOTmh50HJhzA6UlIECDcL6QFuvBu/elaBFxYjbCRTqsbirAuwjGWnzFG94\n2AqsXCua6AyAh4dAF16i5HwZAk9NqiKyrAK0ch345FvJXlLEcO8Z8OHXoj/A6HBgj2gPVF4FHrFG\nf/wUJWwR3dbWhuuuW0hf6+rqwpYtW9DV1YX29nYcOnQIR44cCbvt8GFjQj/mSUQnOqScw2WsR7Qv\nLasBHcmFPDurOsx1YYrRdUsjwLW9L0K77xswfewzMN34EdCFlyiLtkBYB4DqIHpoQA1hRtqJ7u8G\nMmSoUDcWkXTAYQ8c2LMIuuQKcOcb4DS46WCXE6Tjs4Dy8oC8/JDWmUIQRqzqMbkBTkPpAjvGoP33\nt5O9DOMZsYJWrgXmZoM3qdIN6wBQWaOG+Wvqgemp9HPiGeoHThwBT09F9/5QUg4gY6O/I9JEMzNc\nLheKioqwe/dubNu2DQ6HA06nM+y28XFjf1l8O9HKI9pAZw4voaK/3ToDFqJAd3KhbUDd+eblhT7e\nuguBo4fBmqY8On/zKPgXP4Lp8/8EOn+T2ufd28HP/SZg0cK2EEOFAFBUBJxzR6RhzRSP6IiwlC77\n4UIeH1NDlmGgomJQx0bwvhcTsKoYicSpRxw6IoaZPYXXuuX1ves+CX7t5YySgLE25zEBqFZyvkzp\nRlsHVPEMT6ryyrVpZXXHU5OqEdbYAkTZRWf7MChEJxqlZcqqckbfvFe6EFERTUQwm8144oknsG3b\nNtjtdpT5PhBRAAAgAElEQVSUlMBisYTdVloavvsUET7R34Z7RHsxlwbVRMdTzoGGFcp9ZPJc6P3C\nOHN4odIKpe8+cxz88HfB+/fA9OVvgRoXhrqoug60fgt456+XHsA2CATziIZyVEBhkW4j9Uxz5tAL\nlZSBl30nekylN+qAtl6THpKOSIpoceiIHLcTyMoCGpqBseUzWMj9PcDsTGY9vbKPAsUWUE4OqL45\nYxw61FBh/fy/Kd100VZlHEAdF4GPHIjuGPYwcg5TFlBannGSrOxIdmZmdHR0YN++fWhpacGDDz6I\nDRs2wOVy6dq2mM7OTnR2ds7/e/v27TCb9f0x4uJijE+eQ3EWwWkfRlFTC7J0vlcv0zV1mD5yAMUB\njuuaOoe8ymrkGHxOL87mNuRb+5HTsfT75uWcbQBobUeBjjVMXHgxZr77T8hadyGKdnxXDTAuYu6W\nT8D1lb9G0Y1/BpO5ZH67y25D3qbLQn6tDksZinhO189AG7XBmZsHS11D2H2TRW5uru5rUS/nKqtB\nU5PIj9M1kw6cm3SDKmt0fQ94y+VwPHIvCh2jyAqjoU4m4xNuFNfUwaTn97CmDlkTTuQZcA3E4xpN\nRWZt/ThXXYfiukaMn5tAcX6e8U5MKcjEyBCmARROuJDd1JLs5UTF4mt0tuckztXUw2w2Y6q1HXP9\n3SjMgGt4YtSGrFVr53+vZy/chHM/ujdtfj+nHaOYaViBvE2X4dwj90e1brdzDNkdF4X8bHNW1SL/\nnDtudVO0PProo/P/39HRgY6ODt3vDVtEd3d34/HHH0dvby/uv/9+bNy4EXl5ebjjjjtQV1eHzZs3\nY3Z2FocOHQq7bTGBFut0RpBiVNMA5/G3oA0PwZ1fBIrkvTrg7Fxo9pGAa5obt0PLysakwef0ol14\nCSZ+90uYAkVIe9dw+jjokiswq2MNfPHlQH4htHd/EK6ZWWAmwHsKioGLLoXzl/8Ppps+unCe/l5o\nxSUhv1atsBjuoQFQSRCjdd+1HDsCrm2M7GedYMxms+Hr0wqKAOsgZlL46443mm0IaFuj/3uw+Qq4\ndj4F0wf+Ir4LixLW5sATLriYdX3+aMUlmBnow7QB10A8rtFUhLvPQCuthMvtBkrK4Ow5G1peliHM\ndZ8CSsrh7j4Nk44njqnI4mtU6zkDlFbA6XSCK2qgvfIc5jLgGp7r74Zp49b532uuqofW1w2HzRqw\nYZVqaGdOAhXVmKttgtbfDcdgf8AAt1DMWQcxd3FxyM82raQME71nQ9Y1icZsNmP79u1Rvz9sEd3c\n3IzPf/7zftu2bdvmf5DsbNx+++1htxkN1TaAT3QBuXnxuVAtJcGHgOKVWOiB3vEuaF/5q9DuG33d\noBv1SSKotR3U2h5+v3dvh/a1z4HfeSPIbFEathErEM79pFi/Q4dy5lhmQ4WA0kTrtS7MUNgxBlNJ\neE20F7rsGmj3/CP4/R9RjwNTjXMTQH6h/rWVVy77ayBSeGRoQa5XWq485lO0iGZmpYk14Djo7wFd\ndKn6/M0UhocW/pZ4NNFGfc+SitfezgPl5Cp98eljwLr1Id/KozbAOQ5asSrOiwzBUD+wugOUnQOs\nOg946zAQKvcgEKO20IOFQEba3KVl2Mo8NQ3gzv1AhfH2dgDCu3PEs4jOLwRdeyP46Z8HfJ2nppQG\nyecX15DzVlSDLn4b+JlfqQ32EcBcAsoNM7xotugPXFluHtEeyFIGXuaDhXCM6XLn8EINzSoBrMuA\n6Pp4EGFyKZVVpd/UfrIZXhgcT+XAGu2n/wX+6QPGHMw5pvz9W1erwjNT8PlZwlIKMILPHaUJPDUJ\nnFP2dr4oq7vwumh+7IfQngr8dz5RsLUfVKPklbRufcS6aGZWtUKowUJA/eyliE4h6hqBY52Gxn37\nkVcAaJr6JfGBZ2aA2Vll/h9H6B3vBh97E9x7ZumLgz1AdZ2KJzf6vO/6IPjF34MdY/MDB2GJIHBl\nuXlEz1NSFvymbLkwbtflzuGLGjBM0RhwlyOy5NJyceeIFB61gbyFV1lFSg4XanueBx/aB977kjHu\nAwO9QF0jqLImo7x11VMF1fQiImVz2pfmw4XWAaCyVtnb+UCrwvtF8/AQ+OBe1VgykIi96If6gBpl\nHkDnrQcfibBp4XIoRUBefsjdqLxKdd4ziLQuoqmmAZidAZXHwZkDnl/yQN1ot+o+xfsRFOXlg659\nf8C7VBX33RKf85ZXgTZfAf79r8Lb23kptujyv/U+pgzrbZ2JlIR4srEMYE1T10gEnWgAoM2Xg998\nPXgYUDKZcEXUiUZpBTA+qmRSgj6Ghxa6l6UVKXcTwgM9Ksb+b/4BaGoF3nzdkGNSXZP6ujOtE+0j\nDcwIhw7rAFAdwL1q5Vrg1NGQFoX87NOgK64DRofBM9OGLIdPH4O24zO6C2l2OYC5OeVGBijHr3MT\n4Eiuu3Ae0V4y0Cs6rYtoeB4/IB72dl7MAXTRcdZD+0JX3QCcPALuOe3/Qt9ZZfkUr/PecDP45Z3A\nibf0daLNOgNXxkaB7GyQOYLuXaZQbAEmXCokZzky4QLy8lR6YwRQkRk4bwP4tT/GaWHRwy5nRAM4\nlJMDFBYv65upSPB6RM9/xpdVglPIIounJqE98G+gmz4KampVN3yvvhD7gQd6AW8RbR/OiJsunp1V\ndn2+j/wzwCt6sb2dF7KUqiCyIF8fT7jBu58FvfNGdWMx1B/7WjQN2s8eVPWB3ic2Q/1Adf18U5BM\nJo+kI4JutN0WXsoBeCw+bRmV2prWRTTl5ak46njJOYDARXQ8PaIXQXn5oOtugvbUz/y2q050/Ca2\nqbwSdOlV4Fd26dJdU7EFrGewcBn6Q3shU5a6blwZktIVKTqDVgJBF1wMHH3T4AUZQDQ31GXiFa2b\nCRdAJlCh6vZTmWewMAVgZvBP7getWAl6+zsBALRxK7hrP3hyIrZjD/SA6hrVTVexRfkrpzv2YcBS\n5idBzIhO9FB/4E40PJKOIH7R/PJOUMdFqn6pawQP9Ma8FN7znPqfdeuBnlP63jO0oIeeZ916IIIi\nmkeHQTo60VRQqDzfU/GpYpSkdRENKP0u2tbG7/iWUqUN9sUd2TBRzGu48nrg1DFw98mFjX3dKpQl\nnue94QNATi4oyAeEH2Z9mmgeWKbOHF4sZaqYXI447EoXHgXUtgZ8+qjBCzKAaIvoFJMkpCzDi9Jo\nyypTp4j+4x/AZ06APvzphS5esQVYdR74wKuxHXygR3WiAdWlHMkASYevM4cXH4eOdIVtA8H/Rq5c\nGzABkOfmwM8+BXrn+wBASXdi1EXz5AT4V4/A9KefAjW3gbv1FdEY6p9PW/RC6zaA3zqkPy1zNHTQ\nih/lVcBI5uii076INl15vXpsEi8sJUsevbLbCSpOnFk45eaBrr8J2pM/85zfpay1yuPYgYdKOjTt\nuBdobgu/s97Bwl59KYsZS0lpZiWQRQA7xqL/Xa1pANzOpTe0ySaKIprKK8WhQy8jQ/6D457h3GTL\nG7j3NPgXP4Lp03+/ZJiKNl8B3vtS9MeecKvPd09RQhXV4OH0Hy7k4aGFAVEPZCkFsrKB8TTutA8N\nLClCvajhwqWdaH7jFfUUvXW12lDXCAzG1onmpx8FnXeROmZT21IJaDCsAYroiiolO9Nrx2kf1l+P\nZJjNXdoX0XHHXBpEE51YTS9dcR1w9gT47AlP3HfTkmnguJy3qlbfAGWxRZdMgXtOgfQU5RkKWcpS\nrxBMFBHa2/lCJpOy+zqVYt1olxOI9IZaor91wyO2eTcHAMrHtii5mnKenID2wDdBt9yqOoiLoA1b\ngBNd+uRtgRjoAWobFz7fK2syY7jQV9vuSxrrouft7UqDhIzVNgITbj9rU2YG7/w1TJ4uNKA60RxD\nJ5oH+8B/3AnyhKRRc1sEco4+UICbgEis7vTKOYDMc+iQIjocgdw5IvSGNQLKzQPdcDO0J38G7j8L\namxJ6PnDkpcPsMe/Ogg8O6PutuPkKpIWlJQpm7flyHj0cg7AI+lIsSKa3a6Ik71QVgm2Z84fkbgy\nskjOASRV0sHM4B9/D7S6A6ZL3xFwH8ovAJ2/Cfx6dIOwPNgLqmtc2FBRnRmBK4HkHACovil9ddFB\n7O28kMkEtK0BfHXRJ99ST203+KQ41zYC1v6on7Boj/436PoPgLyfrzX1wLhdPdUIATN73EWCFdE6\nddH24SU+2UEROcfygswl4ECd6ATKOebXcvm1QM9p8O5dKTecR0ThJR0DvUBFjRoIXa6ECvCJM5xs\nLanDHnUnGkjNIjpaOYd0ovURSAIwn1qYDI51grtPgT70yZC70ebLwftejO4cnk70/LEqayKzG0tR\neMQKChSMVt+sbE/TEWvwoUIviyUd2s4nQNve65dySnn5yskjCtkOH34dGOoHXfOeheOZstTMVG8Y\nScfYKJCXDyosWvramguAE0fC+p6zpik5jm5NdKXIOZYVAaK/2R2ZrZVRUE4u6IabgdPH4urMETXF\noZ0nuPsUqGn5SjkAqCIySZ1o7V++mNQiVGmio+9Eo3W1kjSlkt2XyxH5DXVZlQwW6iWABEClFiap\nE31gD+jSK8MmuKJjE9DXHZX2nQd6/WUilTUZ3oluBuvV3qYYbB0IaG/nC61ccOhg2yBw7DBo6zVL\nd6xrVI2mSM4/OwPtf34A0y23KqmT73mbdeiih/qC67mLitVw66nQgTFwjAEFRSrqXAdUIXKO5UXQ\nsJXEF9EAlJXShZfoG/ZLNOYSIJQOsOdUaq47gVBJGTgJg4U8M6P8Zg/HHgQRNePRa6IBj190aXlq\nJZxFGrYCqK/B6Vi+fuGREFDOUQEkwSuamcEHXgWt3xJ2X8rJAW3YAn4tigHDgR6V5OelrFIF9KTx\n9cIzM+qGs6x86Yv1zcBAT3o6dAz1zyf9BaWlHeg7C56eUo4cb78WFCDtmOqawIORdeR519NAVS3o\nwkuWvtjUBoRx6Ahob+e7pnXrwV1hJB32CJw5ABksXHYUeQIyfLtfbldS5ByA+nDO+j93JKUTHg4q\ntqj0oyBw98llPVQIIHnR36M2gAjc+Ubiz+3FYVfuJDFAbWtTRtLBs7PA1CRQEOBRaAgoK0vdcKaz\nI0EC4AkXwKxcAnxJVmphf7daj855lGhcOnh6Sj1ir1oozCg7W1ljpvPTixErUFbpJ2HwQsUWICc3\nLb8+legbRs6Rl6ekFUcOgl95DvSOdwfesa4xIps7HreD//dxmG65NfB5m9vA4YYLQ3SiAZ3DhXrT\nCr2UeJsIoWUi6YIU0WGgrCz1Ie5yLmx0OYHC1Ctik04Ihw7WNKD3jIrFXc4kyyd6xAqsXAcM9i7V\n+CcA1uY8swQlsR2obU3qOHRMuIDCYn3uNYsRXXR4PB7Ri7+/VFaRFDmH6kJv1v/zXnuBevoz2Kf/\nJEP9QGWN+rvjS2Wax38HeqLgS7o6dISwt/OFVq6D9rMHQRdsCupiQbVNEQWu8K8eAW3dBvLRz/tR\nvwIY6gtZrIaVo6xcC/T3qBvaYMew20ARdKIpK0s1k5I9o2MQUkTrwbzgFc3MgDsKHeRywGwBnM7A\nrw0PAQWFquuwnCksAmamVMcpgfCIFVRTB6w+H9ylz7bIUFwOpZvzSSuLhpQaLoxhwFjpeqWIDsmI\nNaCGNmlyjoN7lX2dTsiUBbrkcvBe/QOG3N/tL+XwHquiBpzGumgeHvKzKlxMOiYX8uS50PZ2PtCq\ntcCIdT5cJSD1TcBAry5ZC8/MgF97GfSum4OfMy8PqKgJPbQ51Kc8+IMdIydXFdKh0mLtI5HJOQCP\npCOyzz9mhvbSMykn+5EiWg++0d/TUyqGNtxgyXIklFd0zyml0VrmEFFyHDqGrcoZ5fxNwJvG6KK1\nZ58CH9ijb+fxsZjs7eapbwbGRsDuIDdriSSW2YhySS0MB48EcOYAPHKOkYT+MeWxUVVwtHdE9D66\nRLl06F7rYG9A7+n070QPZV4n2jYY0t7Oj3XrQTf9BWjFqqC7ULEFyNYZPHP2BFBTH1bWSSFCV3hu\nTv1dqK4NfYzzwkg6IpVzIEqv6HE7+Mf3ppxFrBTROvCL/nYlb6gw1SFzSVBNNHcv75AVPyxJ8Ioe\ntQIVVaDzN4I79+uPcw0Bd+4HH+/St3MMQSu+UFYWsGIVcPpYzMeKmVg+C0TOEZ5hq39aoQfKLwBy\ncpScJkHwoX2gjo2RP0lpWwPMzuoPvlhkbzdPujt0DAd5quBBdaLTzOZOh72dFyoshumGD4TfUadD\nBx/vBOm5oQsVujIyBJSUhXXVCOcXzfbhiOQcAKK7KfQ6uAz1R/a+OCNFtB4spYDTU0SLlCM4IXyi\npYj2oaRs4XpKEDysPFqpskYVfjr/qIfENgC2Duo7/7g9+sjvRaSKpCMWq0sqq5Lo7zDwiC2wrzCQ\n8OFCPvAqEIGUwwsRRSbpWGxv5z1ORXp7RSs5R7hOdHo5dOixt4sUpYsOfzPBx7t0FdHU1Bp8uHCo\nP6SUY57GVsDlhPbLH0F79QVwz2nwzPTC61F0olHfDO47E9FbvPvzUGzx6EYjRbQezCWAwyNTcLuk\nEx2MYktwi7ue0yLn8ECWUnCihwtHF7p6dP7GmK3uWJsDbEOAbUDfGxyxpRX6kipFtMg54szIUOCY\naEDpohM0mMRTk8DxTtD5G6N6P22+ArzvpbBPf3huTkkEagMUNpU1UQVxpAwjSk4WDCoqBgoK0sv6\nTI+9XaTo6ESzNqcSENvPC3+8pjYV0Bbg2lNx3+HXTyYTTH/7VSA7B9i/B9oP/gPaZ/8Mc//wV5j7\n3tfVU0YdunC/Yza2Aj1nInoPes8CVbUp14mObcpnuWApnXcEYJFzBMccuBPNDjswM62GCYSEB67w\n7Kz6oPM8cqPzN0F7+ufAn9wS/UFHh4G8PGB4CMwc3rHAMaasjYygbQ3ww3vAmqZPjxgvXDEkl5Zl\nVmpXXAjh6EClyqEjCl+UyOk6ALSuBi222tMJNbYA+YWq8FkdontoGwBKywPP25SVA65x8MwMKCdn\n6espDE9NARPu8DfRXl10KO10CsHWfpi2XGnoMamuCdqBV0Pv1HsWKCnV9WSPzBZ17Y1YVQHqy1B/\nYOlQoOOsXAtauXb+3zw7q67X/h7wRZdFLnOqbQDGhsFTkyqtUQfc3w3auFVXpz6RSCdaB2QuWdBE\nu53qrllYSqEZcDuX3vV2q5CVqKzAMpGSMtWZTRT2YcBStmCbtboD6D0DdsegKbUOqC5HTo4+aUqM\nQSu+kKVU3cgORWAdFg/cUQSteLGUAufcYSN1lys84QLmtOANi7LKxHWidQashIK2XgN++ZnQOw30\nBi1qyJSVvjdeo1agvCrsDW+8kguNmP8IiHVQl71dRNQ1AoNhOtF69dBemgOHrqiglejWT9nZoLom\n0KatMG29OvL3Z2Wpa13nz5u1OWCgB7TxMiASy8gEIEW0HiylC+4cMdhaZTqUnQ3kFywZ+BE9tD9k\nKUusnGNRdDLl5CqXgXAm+iFQesA6FQphC6/VZIcdFGPQii/UmnxJB7sdKowpCshkUp15kXQEZsSm\nBmGD3XgnyOaOtTnw4ddAGzbHdBzaeg344N6QrjLc3x3YmcNLRbWSuKQbQeK+lxAHhw7uPQPt7z4O\nnnAbe9wI7O0ioqwSmJwM7ct8vDMil5igumi9mug4QY2t4N4wseRerINKVtvUBozaUiq9U4poPfj4\nRKuJ/GXudRyK4pKlko5usbfzo6Q0oYOFPGIDlfs/IqWOjeBYrO5sA0BVHaiqFqxHF+0YU64kRpEK\noStuV2xPpUQXHZww4RwqcCUB37uTR4GS8sBWexFAZgvo/IvBr+wKvtNgb0CP6PljVKbncCEPW0MP\nFXow2qGDp6egff/fVaro2ROGHRdAZPZ2EUBESuoQRBfNzMCxTlAoWdDiYza1gRd1onl6Sn0mB3C/\nSRhNLfp10X1ngcYWJWUqqwCG9Q20JwIpovXgcedQQSvO6B/hLgcC6KK55zRIiugFEqyJDjSgRRds\nBL+5P+ppeLYOqKGUylrVJQiHw26YnANIkeHCWDTR8ASuiENHQHgkTOGVoMFCPvhqzF1oL3Tl9eAX\nfh/0d44HeoOnzwHqpiIdhwv1dqLrmoCBHsPkF/zYQ6CGFaC3vxN8xuAi2toPGOzM4YXqQjh0DPUD\nObmR3dQ1tarBfl+sA0BVbcAY9kShOtFndO3LfWdADSvUP2oaUmq4UIpoHVBePkAmYGpS2VqJnCM4\nixw6eHJCPXYNNHG+XLEoTXTUBexgHzgSn+QR25KuHlXXA7m5Koo9GqwDyiO1ujZsV4BnZ4FzE8bK\noJpaANugur6ShTvGp1LpqnFNBMOh3RxQmiA5x8G9oPXGFNFoPw8gAo51Lj2PpqlOdCg5R2VNWgau\ncLigFQ9UWKQ08AH8sFmbAx94VffnHh/YAz78OugjtwEt7eAzxyNed8jjD/UrOVs8COHQofTQOlw5\nfKmsUbWL0ycIbUi/x3XcaGwB+s7oS2jsOwt4imiqqQenkC5aimi9eCUdbqcaoBMCQsUW/8CVnjNA\nw4qFoTZBhUWQCZg8F/F7ecQG7T/+AdrT/xPBe6wBOxd0/ibwm29EvgZNU4VzVR2oshZsC9OJdo4D\nxSWGdj0oO0d1WE4b+8cxImJ9KiVyjqDwSBhf4SIzMDOjtKnxWsNgr/odDZEyFwlEBLriOvCLv1v6\non0YyC9UhWSw91dWp2f097A1ZOS3H/VNfrponpmG9uLvof3j30L7zaPQ/vNr0HaHkMQAYPsItEfu\ng+mT/xdUWARqbQcMLqJhHTDe3s5DyE708c7QDi+Bjkfk6UYvSDqUvV1yG1tUbAHyCvTdGPZ1L3Si\naxuSP1TugxTRevFGf8tgYWgWBa5w9ymRcgQiiuhvdjuhfecu0IZLIxvACaIvpfOj1EWPjQIFxeoJ\nTVWt0geGwmEHLCWRnycMyZR08Mw0oM0BOu2ZAkHlqSPn4FEb+HgXuK8bPDaiNJPJZMQKlIfQRBPF\nPFzIXQdUoRzsdU8X2khXIbrsavDh1/27ggAw0BNSDw1AdebTsBMd0u97EUoX3Q12u6D99jFoX/4k\n+MCrMH30b2D6yr/D9MVvgJ/6GbQnfhKwg8naHLT/vhv0jncvWLJV1QGT55TVqkGwtR9UFcdOdJDr\nko9F6MzhgZoX6aKH+o13FomGplYgTOgKT0+pJ3aeop9qGsApVESLT7RevKmFMeogMx5zCTA+uvDv\nnlNA6+rkrSdVKfFEf+v8IOOZaWj3fh10/kbQzR8D/58/6PLYZG1OFRqBEqXWXAA8+O/gcxOggkL9\na7cNKBkHAJSWAxNu8NQUKC+Avy2gvk6DglZ8obY10F55zvDj6sITtBJTgVVWlfRONM/OgJ/5NXjn\nr5XGc8KlrPsm3Ep6UFQMFFtg+sydoEhTyWJhxBa+8Cr16KJ1et36wrOz0H7wHwBroOs/AHrn+5Y8\nKeEDr8L0ru0RHzsUVFQM2rAFvPtZ0HU3LZwrnB4aUL9DE27w9FRgL+kUhM9NANNTgFnnPER9M/jp\n/wH//legCy+G6fYdymfbS10TTF/+FrTvfV11gz/2Gb/Yav79r9TP9F03z28jIqBlFXD6BLD+EmO+\nsHjY23mpqgPGRpf8nHnUpoYko7je0dQKdO5fOJa1H6at1xix2pigxhZwzxnVGArGQA9QXbfgRV3T\nkFI2d9KJ1sl8ytyEC4jSdH9ZsLgT3XMK1NSaxAWlKJZS3V7RrM1B+8HdoLIK0M0fV3/sqxvUh0s4\nxkaVlCJ7aUAD5eUDK9cARw5GtHRfPSCZTJ6Bp+DdaHaMgYx05vDSugY4+VZyooKNCF0qr1ShNUmC\nT3RB+9rnwMe7YPqHu5H15W8h62v3I+vuR2C6/xcw3fNTmP7hbmXFd+qtxK3r3IQKZyoOrTdXDh1R\ndqKPHACq62D6yn+AD78O7V+/BPaVETjHlSPA2gujO34I1IDh7/wH6AZ6Quuh4fldK68KqBlOVTTb\nIFBRo/tmkzo2gi69CqY77oHpE5/zL6C9+1hKYfrCPwNzc9DuvgPsmcHh08fAO5+A6dbPL7khIgN1\n0XGzt/NAWVlKx7xoeI6PdwHt50V1456ynejGlrA2d9x7FtTQsrChrEJpvA22LYwWKaL1Yi5RE7m5\neQELEkFBxZaFD7XZGfVYyvcXQACg3yuamcE//4EK+fn47fOWSt7HnmEZtoa0MaLzN4E7I9RFW5W9\n3TxVtaHjv8eNdebwQuWVQE5ueDlJPIglaMVLsQWYmVax0gmE3S5oj9wH7YFvgv7kQzB95h+XaFaJ\nCJSXp27c2taAI43ojQWP/ChssRDDcCHveR605SpQVS1Mn/8aaOs10L71FWi/eRQ8Nwc+9BqwbkN8\n0gHb1igZ0FuHFtYz0AMKJ+cA0i7+W7MORJRASGUVMN34EVAY6zXKzQN96oug9g5o//pF8Jnj0L7/\n7zB95NOgAMm4RhbRsA7Exd7Oj0C66Ait7fyobQJGreCpSRWyNT0dl6eDkUKBnEMW03cGaFyx8B4i\nNRSZIg4dUkTrxVIKHuiVyO9w+Frc9feoLkSwx/zLmRJ9nWj+/S/Bx96E6bYv+/9BXzSAE/T9I1ZQ\nCJcDry46km4u2wb87J2oug4cKnDFOa6+3njQtjo5uugYgla8zOt6E9SNZmZoe1+EduffAiaC6Z/u\nhemSt4ctVqmpJXBYQ7wYseqzRIsytZAnJ5RzwyVvB6A6vKarboDpq3eDj70J7Rv/F/zS741z5VgE\nEYGuvB6aZ8CQmZUbQ134x/RquDA+uuiou/oh0GyD+ocKI4RMJphu+ijo+g9A+9cvgdatB23cGnjn\nFjVcaMhTq0Wff/GAAjh0KGeO86M7Xna2KqR7z6hmYE1daiQIV9cD4/aQA8Lcd3ZhqNAD1TamjC5a\nimi9mEtUV1WK6ND4yDm4R5IKg2IpCztYqL3yHPi538L02btAiyRE1NAM7tPRiR4J3YlGbaNyCtEj\nDTfEEyQAACAASURBVPHiTSv0UlmjoxMdn64HJSl0hd0uY6wuyxLn0MEv7wQ/+TOYPv33MH3400uu\nqaA0tkZshchvvoG573098kXCE86hIwQi2sAVfuMVYHWHcgfwPV5FtdLgXnUD4BwHXXhxxMfWC225\nCjhyEDxuVzeZzPp0w3GyueMRK7Qv3Qp+Y7ehx9Vsg7qHCqPFdPm1MN35HdCHPhl0HyqrALKyDZHC\nxNXezktdE3jAV17kUE9dmlqiPqRKLjydEs4cXigrS8mYQsV/+9jbzVOTOg4dUkTrhCyl6sNLhgpD\n4+sT3XMakCI6IFRSpv6ABoH7usGPPQTTZ+9UfwAWozcid1Hk95J1EEWUXsjM80b988eoqgtpc8cO\nu/r9iQNJc+hwGRO6ROWViUneA8DP/y9MH/rLBdcCvVTWAOfcISOrl5zr2JvA4deVvjlSRkOnFc5T\nVqE0/xHCe56H6dKrAr5GRDBdfi2yvv5fS4psI6GCQtCmt4Ff3unRQzfq6wzGK3BloAeoqoX2yH1K\ne2sQ8exE+0J1TX4DhgExyurO08mNJ0s60Se6gJVrY7MJbW5Tg/6poof2oIYLA0s62OlQg6mLJTo1\n9SkzXChFtF7MpQAzSDrRoSkoBGZnwDPT4O6TYm8XjDAWd/z7X4KueQ+ovjnwDpU1gGs8bNgIj1iX\nRH4vRqUX6tRFj9uBvHx/P9uqGiCUnMMxFj/9XfNKlXKWaEs2A+QcAJRDRwLkHHz2pHpCdN6GiN9L\nJpMKRginXfQ935njKsyna3/4nRe/N1zQipeyioi7+Dw2Apw9CcRJqhEJdOX14JeeAfd3B/89X/ye\nOEV/82AfqGMDTH/5BWj3/4u+eQsdqMHC+Hai9UIt7eAYfeWZGfzWYVBLnB2nahpVmNTcnDrvsU7Q\nqghDVhZBTW2qWE2xIhpNrUCw4cL+s0B985IbTKpNHZs7KaL14vW5lSI6JETk6UaPq0fA0okOjKUs\naPQ3jw4rj9qr3hX07WTKUlKM/jAyjDCdaADAmguBU0fVIGg4vEmFvlTWACNWZacXiPGx+Mk5cvNU\nVz7RoStGDBYCQG1DZOmTUcIvPwN6+zuj7mRRY2vQbtGSczEDZ0+Arnkv+ODeyE8WLvLbi6UUcLv0\nXbfetb36ImjjZeG7lgmAVqwCii3gXb/Rb1tWWR0fd47BXqC2EdRxEejmj0P7zg5DNNJz1gF9+vYE\nYMhw4ZnjgDfoKY5QXp66vj1P+Ph4J2h1dHroeZpagL6zaog1ReQcQOj47yXOHF480d9GRcTHghTR\neikyK+2oEX84M51isypqCoqkcx8MSyngHA/4IcDPPgXaejUozLVG9StCdoxY01SXM8C0ut9xCgpV\nYXz2ZNhls21gScgA5eapGyf70kfrPDMNzEwBIZLYYoXOuyhyh5EQsGMsbAHBLqchmmjauBU4fSyu\nMbY8NQne+xLobTH4wuqZovdiHVDpe2/fpoJFgt1cBUNvTLQpS/0ehZBFLYb3PA8KIuVIBnTl9cBg\nLyiMvd085lJgetLwpEYe7APVqsLKtPVq0FU3QPvujphsxHjCBWha6jSeWlYB3Scjvx594L0vgXQM\n4xpCXRMw2KOeNg72quHIGKD8QuXr33sm7oOREdHYoor7QAXxImcOL1RQqJ56RyHnMhoponVCJpNy\nnhBNdHjMJeCu/dKFDgHl5CibqwmX33aecINf3gna9t7wBwmni3bYgcIiXcEMtGod+OSR8OcMFndb\nFWS40DEGWErj+keHLtgEPhxF8mIQ+IXfgX/5o9A7TRjgEw3VcaIrrgc/+5Tu9zAztKd+Dm1x6l2w\n/V/7o9JThrmZCgU1tYb1c50/35njQEu7ipovKYto8JMnveEcOhMuI5B0cO8Z9XOLIvEtXtDmK9QN\n6OLBqWD7Eympi9Hd6KE+JSHwnuf6D4Daz4N23zfAM/o7/X4MD8FUnSIuEIBq6JhLotbSsqaBX3sZ\ndPHlBq8sMFTXqBzBTh4FVqw0xG6RmtqAYkvYBk0ioaJi1WQJIFMK5MwxT019SgwXRl1EP/zww7jr\nrrvwjW98A7Ozs7jnnntw55134r777gOAgNvSHnOJMTrIDIeKLeAjB0UPHY6SMiV18IFf/B3ogk2q\nAAlDWK/oEZt+PeLKdeATOovoAHG3QYcL4+jMMU/basA+bJxFl3MMfOzN0HZYRoSteKB3vAu89wX9\ng3sH94Kf+hkmHw9T6Hvgl5+B6fJrY1ghgPoVwGCfPunEmROgllUAAFq/GXxwn/7zjNiAch0e0V5K\nK8ABnoAEQnlDXxlff98Iobx8mL75UGRpkAY7dPC5CZVQ6TPATETK7aKwCPzDe6J7bD5shclnADkV\niEnScfIt1ZRo0Kdfj5m6JjXvcawTtMqgG7+m1tTSQ3sJ4ADEmgb0dQe9waSahrg+wdNLVJ8mDocD\no6OjuOuuu1BTU4Pf/va3aGhowI4dOzA4OIi9e/fi+eefX7It7amoBpWWJ3sVqY/ZAtgGQc2SVBiS\nRamFPDOjpBw+ccAhqW8KqYnm4SFdxTigOtE4cSSsjypbB0CBHgVW1QYOPXHEJ2jFFzJlgc7boNth\nJCxOh5LBhCpU3C7jiujSctCGS8Ev/C7svqzNQfvVI6CPfQYzu3eFHQDj/m419HlBbHZtlJenbsgG\ne8Puy2eOgzyPnunCSyLTRevR8PuuS2cnmjUNvPdF0JZ36F9LgohUn00V1Wr40iiG+oCa+iU3F2TK\ngukvvwC2D4Of+nnEh+XhIZiqUkMPPU9L9A4dvO+leW/xRODtRPOJGEJWFh/zoktBV95gyLGMROmi\nFz3pGrUBBQXBJaG1qWFzF1URbbFYMDk5iYMHD2JsbAxnz57Fli1b0NXVhfb2dhw6dAhHjhzx23b4\n8GGj155wTH/993GJgc04vNZQTSuTu44UR0XJ+xTRe18A6lfoj0mvqAYmXMF1i6MRdKLLq5SPaiir\nOmZP0EAgOUfgIpodY6BEJGNdcDH48GuGHIqd4ypc6dibgV9nVu4cBkq76J3vBT/3m7CdXt7zAlBY\nDLrsauS9/yPQHnso9P4v7VT6+uzs2NfY1Bo2uZDn5pR2eoXnd791NeByhLRA9Hv/iFX3jR8Aj82d\njicQRw8DZkviuojxxOhO9GAvKMhgI+XmwfSpvwPvelppnCNhxApTgKdWySRahw7W5sBv7E6YlAPA\nfCcaZ08CK9cYckiqb4bpstS7kURjy9LPlkD+0D5QTWo4dET9XKu5uRlPPvkkWlpa4HQ6UVRUhN27\nd2Pbtm1wOBxLto2P69PvpTKUk5My+q6UptiiunSRPKJcjpSUzXeiWdPAv/8VTNfr7ELDo9OvbQyu\nix7W6bcLz+PbVWEkHS4HYMoKqKejqtogco6xuHeiAYA6LgLeOhyRU0NQXA418Hc0yI3/1KT6Phjo\n8ECNrSpgYd/LQffhmRnwkz9VKW1EyLv2RmB4KOjNA8/MgPc8B3r7O41ZZGOL8pkNxWAvUFo+H+RC\nJhPowovBh3RKOvTa23kprdCVWsivqpjvTMDw1MLBPtXVC3a+sgqVbPryHyI6rOpEp5acAytWAv3d\nkX9OHH0TKCmbH75MBFRkBnLzlGtKfmHCzpsMqKllic0d954J7MzhxePQkWyiKqL371fen3fccQd6\ne3tx8uRJPPnkk9i2bRvsdjtKSkpgsVjwxBNPzG8rLY3/H1IhNaCSMqC5TW44wuGbWnj4dSAnJ+In\nHaF00Tyq0yrMy6p1QKjhwqH+wF1oIKlyDsAThlTbAOjRdYfDOQ66+G3go4E70UZKOXwxvfNG8M5f\nB5XU8Av/CzSsALUrv1jKzobpg5+A9uh/g2dnl+5/YA/Q2GJYuho1tQW1opo/55njyrrN930RSDp4\nZCh0wubiNZWFD6vh6Snw/j1qiC8TqKg2NrVwsE8VJCGga96jnpTodLbgyXPA6WPISrHhcsrLV59V\nkSZwJnCg0I+6JsOkHClNdR3gGPMPZwrTiUZlDWAfiX7w1SCiesbX39+PkhI1Pd3e3o6VK1eis7MT\nLS0tePDBB7Fhwwa4XC7s27fPb9tiOjs70dnZOf/v7du3w2wW94t0h99+DXjDZpjS+GeZm5sb92tx\nuqYWM2/2o8hshvMPT6Dwxg8j1xLZ4OpkWzu04UEUBlirY3QYRU0tyNL5dcxesAkTL+8M+nVPO+2Y\nqW9CUYDXubgY46yhiACTj8zBPeFCTk09chNwLUxu2go+ehgFl7wt6mOwpmHc7YR5wyVwzM2i8Jwb\nWdX+3bTZ4UFMWEoMvz740ivg/MXDKOg+gZzzN/q/dm4Cjt/9AuavfGv+55mbmwvz1nfA/eLvkPPK\ns8h7181+73Htfha5177PsO+9tvZ8OH94D4qLi4PeIE/0nYFp7fnI9zknb7kC4z/8DoqzTP4hPYvg\n6Sk4Th9H8fZP6L5m5xqb4Rq3h/xZTO/eh+lV61DcpM8BI9XRWlbCOWoz7Ppz2AZQuHINskMdb/3F\ncJaWI//4m8i5OLwuePLZJzF3wSYUNLcia3rakHUaxUT7ecga6EHeBRvD7wyAZ2fh2L8HxV+/X/d1\naRTT174XpoYVoX82GYKzqRUFdiuyqy8AADgGelB405+H/NodVbUoco8jK0bf7kcffXT+/zs6OtDR\nof/GJaoi+vLLL8e3v/1tvPbaa8jOzsZnP/tZnDhxAnfccQfq6uqwefNmzM7O4tChQ37bFhNosU6n\n/mhZIYXJygHS+GdpNpvjfi1ybj60ERscB/ZBsw1i8ryNmIrwnFxRA+2NPZhb9D5mhjY8CHd+EUjn\nMbm8GpptCI7BgYCSDa37NFBWFfz7UlkD1+mFoTIAmBuxYS43P+KvKxp49QXQfngPZv9/e/ceFdd1\n3wv8u48GkIEBhod4CoEQegC2JGQ968g4wklkuVbrOjiNuuzltnJaea1G8U1j5zpYVt2be70a38Zr\nKYkrO7ZX7FY1dW+usJ2kkq2qsoOthyVFSMjWK1gGaQRIo2EGBALO7h9nGBjmwZwzw8ww8/2slRV0\nmHNmM94cfrPnt3+/jZuMX8PZC6TMhPPGAFBZDefRj6FMqK8su69AnZk6JfNDfvle9O3ehRlzPGvC\nqs27gEWL0Z89y/17ZTab4XQ6Ie9/GDd+9BQGl652t6qWXZehtp+DunBJ2F57aUqGlBKOLz733Yoe\nwMiZNii1azA08TkrFsJx8ABEgABMfedfIcsqPX7GSceUlAJpu4peu91v1Y2R/b+BuP1LcfO3RUoB\nOTyC3iuX3Wkzhq+ljkC1dqDfnDXpfUKtuwd9bzdhxoLFga/Z3wf1nSYoT/wf3Lx5M+Zed7W4DEOf\nteLm6i8H9Xh58ihkbj76b0mP/N+0xau0/4+x13AqqEWl6PusDUpRGeTwENQrl9CfmR1wXqqzCtF3\n4SxElvHUUbPZjIaGBsPnGwqiMzIysG3bNo9jW7du9bywyeR1jIjGcXUtVPf8EuLuP4KYYaCbXFGp\n7wodDjuQnAIx85agLyVMJq0hwYXPgFuXeT+g6zJQ4+P4qLwCyO4rGB9Ej9aJjog5Fdomtp4rEEa7\npDl6gXRXjeIFNcCZk8DEINrpmLJ68WJVHeT/fwPycgdEobbZSzrskPvegfLU877PKSqFuP0OyOZd\nEN/8lnbOh3shVtWFpbas+3mEGGvR6yOIlkND2kYoHxuKxeIVkCcO+w2i5bVuyPfehvKD/6tvTEnJ\nWtMFh91na3npsANn2yA2f1fXdWOZEEKrYNLTBZSGWO/3ajeQlqGlOUz2vMvWQL71KmTH77Ucfj/k\ne7shbr3d72bFaBPllVD3/yrox8sjHwR880dhUlI2lhdt7QRy8ibddyLyiyCvdCKaiaOxUzCTKNFk\nWrTA9MwpiDvqjV0jOw8YuAHZN2Hn/FWdG7RcAm0u1Mrb+c+vFXkF3g1Xeq8DmZEJooWiQFTXhlbq\nzmHXSjQCEAtuhfS1ubDPMWWdOEVyCsSd6yHfa3Yfk7/6N4gVa7XX19959/0p5JEPITsvQg4PQ7a8\nDxFqbWhfzzM7QPvvznZgVqFWDm/iebctD9i9UL71GsRd9xh78+OnQodURyDfbdICOh1vJqeF3DA1\nXLkSeFPheMKUpM3N99/x+xjp7IX8z3ch/vAboY9tqhTPAbqtQXV9lENDkMcPMYiOgPHtv+Vk+dCj\n8qNf5o5BNFG0mDOA4WGIuvVBrQT5IoRw1YuesLnwapeuDVru61UE6FzY5ae83ai8Qo/NhXLgBiAl\nkBLBACbU7oVO+1i3vIIS4OYg5MRgpS98jVZ8EXethzzyAaSjF/JqF+RH/wlxb+CPG0V6BsQ9X4fa\n9HOg9QiQmw9RNAXl3Er8t//2tanQPb4A3QvlmZOQ509DfO0BH2cGwZLrVStaXuuB+nyjtsP/648Y\nu24ME7n5kGHYXDi+3XdQz3vn1yCPtkA6en1fb88vIWrXBHzDF23ClKQFaBfPT/7gtmPa5j5Wmpp6\nJXOAzouuJiuTVOZwiYWGKwyiiaJEKDMgln8J4q4NoV3HR4UO3fV2R1UsANrPeVV7kH0OQKpjNcB9\njSMv37PMnasyRySrtIjqpcCZk5BDxjYzSUcvhCuIFkJAzK/xrtIxhekcACAyLBC1ayD/69daikbd\neogguj6KunuAa11Q//UliC99dWrGNrvMf/tvV7tvv+f66F4o1RGou16CeOARnyvYQY1pQtdCeexj\nqH//HYiqJVAe/7v4bJAVrgod1g7tzWKQhDkTYukqyA/+w+t7stcGeWAPxAbj+aWRIsrmBdW5MNIN\nVhKZSE3X7qvdVsiOAO2+x4uBhisMoomiSNn8P7TybKEoKvWzEq0/iBap6Vq+5cTVxq7LwKyiwAHx\nhJVoLZUjAo1WxhFpZi237sypSR/rk8Pu+UZhNC96vCleiQYAUb8R8r1myNYjEF/54+DOMZmgNPwl\nMDgAcbvxCiUBFZQA17ohBwe8viXbz0GUBwiifZS6kx/sBVJTQ/u43NW1UN4chPrPL0J982Uojz0F\nZUMDhGJgn8E0IObMgzQ6x8fRuxINAGLdfZD7f+39RvvX/09rq56t/xOwiCurBNrPBXyIvDkIeeII\nxLIp+l0ibyVlWvnBzs+1lenJZGQBw8PahvAoYRBNNM2JolIth2wc2WNwJRq+Uzomy4cGoH2s3msb\na2QQoUYrE4maZca7Fzp7x9I5AIj5t3p1LpRTmBPtft7iUqCyCmLDgwHLwnmdd+syKM/93HB60KTX\nNyVpeYgT59vggPYGKtDq0YTuhbLPCbn7n6E8uDm0TyssOZDnT0P94XeBPgeUp1+AqFho/HrTwbyF\ngP1a0J0g/brSCeTr2wAoZpdrm4iPfeQ+Jm1XtTz89QZTciJMlM+ffCX65Cdav4MILwQkMjG7HPLs\nKe0+nDt5SpAQIupNVxhEE013vlai9bT8nmjeIu+mJV2XtZXmAITJpAXSPVoOsey1hb7KboC49Xbj\nedEOu0cQjaLZ2sbNa91jxyKwEg0Ayl9/H8q6e3WfN1UBtPv6JeXeKR0XLwBFpVqQ7e+8Cd0L5du7\nIGpXQ4TYkEPkFgDt5yDu3gix+bu63nRMV0KZoaVVjAtk9ZI3+oH+Pp+VViajrLsX8v23x671q3+D\nuOPu6ZM6k1+svaELsIIpD38IsSIKDVYSmCgpgzz8gZaH7qdkpdc5BdFt/80gmmi6s+RoH2m5NvtI\nKV3tk419rCoqFkKeP+3ZOW+yTYWjxncu7L2ulfGLtNnlwOAApIHVCemwu3OiAddKR2W152p039Tm\nRLufO8g/IhFXWg580e5xSLZ71gf3ZzSlQ3ZehDx0AGLjn4U+nvnVUP7hVSh/UJ9QXVLF0lWQR40H\n0doqdJGxebZkJXD9GuTvz2qbXw9/APG1+42PJcKEogClFX5TOuTgAOSpoxBL10R4ZAmupBzovQ4R\nTCrHqPxirSRelMToXZqIguVVoaPfCSiK8UYMeQWAqnqU0JLdQaRzQFsVlD2uINpui3hONODaEFhj\nsNSdo9dd4s59vQU1wPjNhX1OwEczmkThcyV6kk2FblVLgQtnoL7xUy1VxayvQ6fP8QgRctORaWnh\nbcDlLyCvX5v8sT5Ia4fhWs5CmQFx1wbI95sh33kT4s71Hm8+p4OJmwvl0E3IixegHvwvyH/5J2Du\ngrDMT9IhrwBITgGCqMzhVlBsaMEkXBhEE8UBjwodPcY2FbqvJQQwsV70lUvBrUTPKgC6XDmvvdej\nks4BjKZ0GMiLdtrHmq2MXmt+jXslWkqpvUlJjf82vH7NLgc62rVSVC6y/RyCWomeeYuWz9vvhKhb\nP4WDjH/ClKTN8+MHjV3AGnyNaJ/Pf8fdkK1HII9/DPGVPzJ8nWgRZZWQH+/HyE/+F0ae+hbUv/lT\nqC8/Dxz7GMjJg/KNR6M9xIQjFAUon49g7iXuc/KLolqhw1DHQiKKMeNXoq92aRU2QiAqFgHnPwVW\n1UH2O4Ghm0FtEhR5BVDPtmn/iGS3wokWLQZefQFycDDo0mlSStdK9IQVtaJSoN8JabsKpMwEkpK1\n/O8EJdLMQGqaVmJtVqE2P+w2oDC4gEz544cAU5KxDp3kQSxdDfXAbwAjb0isncDSVcafOy0d4s71\ngDkTYjp+MlO1FKL7ivYJW9FsIK8woX+vY4Xy+N/pq6qTXwx0XYZUR3SdJ6WE/M2/A3/xNwZGOYYr\n0URxYPxKtOEa0eOvV7FwbCW626r9gQkm3zS3YKx+bZTSOQBom8vK5gGfnQj+pBt9QFKSV6tsoSjA\n6Gp0hDYVxryS8rEWve3ngNLyoP+AiTkVWvURCl1NLXDhM++OpUGQ1rHW8kYp9z8E5e6NIV0jWkRq\nGpT1fwKxbA1E4WwG0DFCb1lKkTJTK0t6rWfyB7vIoSHIV34c2p4CFwbRRPFgfIUOgzWiPcypALov\nQ97ohwx2UyGgpXN0W7WP+qO5Eg2t3JuuKh2+VqFHrzW/Bvis1dVohXmSomSs/Xewmwop/ETKTGDh\nbe6KJ8GS6gjQfVlbxSOa7vKLgt5cKPscUH/8NOTgDSjf/WHIT80gmigeZGYDqgrZe921Eh1awwNh\nSgJK52ptmoOpET163sxULeXhSqe2qptsrAtdOIgaLS/ao8pIIBMbrYy/1oIarblFnyOhNxWOEqXj\ngujPzwW3qZCmhFi6Wv+K2tVuIC1jysshEkWCCHJzoey6BPV/fw+ibD6Uv3rScJfU8RhEE8UBrUJH\nqdYE42oXkJMf+jXnuZqu6FmJBoDcfC0VJBrl7cYrmq2tHPf3Bfd4p93vSjSK5mh1ZS99PuWNVqaF\nEm1zIQCg/SxE2bxojiahicXLgc9O+Owi6deV0DYVEsWU/CLgSkfAh8izbVCfexLi7o1Qvv5I2EqI\nMgmIKE5oedFfuILo0FvviopFUN9/GxgagrLmy8Gfl1eobUrMiG7JKyEEkJ0L2HqCWj2Wjl6/Ja2E\nomj1oo9+BDE7tOYgcSGvAHA6IK0dwMDApI14aOqINLP2ScCpo0BtcHWNjbT7JopVIr8E6t5mqDNT\ngbwCiNx87R5lyYWYMUMrW/jmy1D+/DsQNbVhfW4G0UTxoqgUOH8aGFHDs/mtYiHw8vNAUrK+ICkv\nH/KTFohALaAjxeIKokvKJn+sw7u83XhiQQ1k08+1yh8JTigKUDIH8sO9QNm8hGpyEotErZbSIYIM\nomHtAAq5uZPixMLbIO5/SNsEf/401I/3Az1WbV9OVg4gJZTHn4UI5u+ATgyiieKEKJoNtflfgJy8\nsAQ1Ij1DuwFd6wL0tPPNK9T+SFctCXkMoRLZuZDXehDUq+HoDfhzivk1Wn41c6IBuFr0tuyD+NJX\noj2UhCeWrIL6yzcgh4cCtl4fJa2dUGpXR2BkRFNPJCVBrLzT67gcGtI+mc3I0io2TQHmRBPFi2Kt\nnnHIlTnGEfMWaeXtdOSPibwC7YsoVuZws+QGX/ooUE40oK1mp6YDaazOAUDLi3bYwcoc0SeysoHC\nEuDT1uBOuNIJ5IdW3o4o1omkJIiC4ikLoAEG0UTxw5wFpJtDrhHtYUENROFsfefEVBCdo6VzBEE6\n7AFbFwtFgVh9V8i1deOFmF2ufTGHmwpjgVi6GvLY5FU65I1+bbOtJScCoyKKbwyiieKEu0JHiN0K\nPa654k6IP/+OvpMyLVpXvyg1WhlPZOdBBhlEa3WiA68yK9/YDK68upSUQ6xZx2AsRoilqyCPH9Rq\nQAdypRPILwpbdQKiRMbfIqI4ItZ+DaJqafiupyheHfyCOQeFJUB26BVCQpYdxnQO8iBSUqA88m1u\nKowRYlah9unP+c8CPk5aOyAK+GkKUThwYyFRHFF8bK6IBuWJ56LaaMXNlc4hpQwY7Ekpgd7A1TmI\nYt1o4xVRWeX/QVbWiCYKF65EE1HYxUQADVcHRVOS1mkwkMEbgKKEpYMVUbSI2lWQxz4K3KXT2sl2\n30RhwiCaiOJbMCkdjl6mctD0V1wGKApw8YLfhzCdgyh8GEQTUXwbbbgSiMMOpLN0HU1vQgiIdfdB\n3fkPkN1Wr+9LdQTovqy1SSaikDGIJqK4JrJzJ6/QwZVoihPKunsh6u+D+tyTkJ+f8/zm1W4gLQNi\n5i3RGRxRnGEQTUTxzZIzaTqHdNohJilvRzRdKHfdA+Wb34L642cgTx4d+8YVbiokCicG0UQU3yx5\nwaVzcCWa4oioXQ3lsf8J9ZV/hNryPgCt3bdgEE0UNixxR0RxTWTnQg1mYyHL21GcEfOqoPztD6G+\nsB2q7ar2ZrKwNNrDIoobXIkmovgW7MbCDAbRFH9E4WwoTz4HeeS3kC37IAq5Ek0ULgyiiSi+WXIB\n29WAtXOlsxeCK9EUp0RWDpS//SHEHfXAHLatJwoXBtFEFNdESgqQMlNbbfbHYQe4sZDimEhNg/LN\nv4JIS4/2UIjiBoNoIop/rtVov7ixkIiIdGIQTUTxLzsXsHX7/z5XoomISCcG0UQU94QlB9JP2hc+\nXAAAC3xJREFUhQ45OAioKpDCBhRERBQ8BtFEFP8suf4brji1VA4hRGTHRERE0xqDaCKKf9l5/nOi\nmcpBREQGGG628t5776GlpQVDQ0P49re/jTfeeAM2mw35+fnYsmULhoeHsWPHDo9jRETRILJzofrL\niWajFSIiMsDQSvTFixdx5swZPP3003j22Wdx/PhxFBcXY/v27bBarTh06BD279/vdYyIKCosOX7T\nOaTDDsGVaCIi0snQSvShQ4dQUFCA7du3Iy0tDUNDQ9i0aRPa2tpQWVmJEydO4MaNG9i4caP7WGtr\nK1asWBHu8RMRTc6SC9ivQaoqhDJh7cDJ8nZERKSfoZVom82G06dPo7GxEcuXL4eqqkhLS0NLSwvq\n6+vR29sLh8PhccxuD9DogIhoComkZOCWNN8NVxy9DKKJiEg3QyvRZrMZs2bNgqIoqKysxJEjR9Dc\n3Iz6+nrYbDZkZmYiOTkZu3fvdh/Lysryus6pU6dw6tQp978bGhpgNpuN/zREYZKcnMy5GGccObNw\ny2A/TOZSj+P9A/2YUVqOlGn235tzlGId5yhNB01NTe6vq6urUV1dHfS5hoLoqqoq7NmzBwDw6aef\nYv78+Whra0NZWRl27tyJJUuWwOl04vDhwx7HJvI1WIfDYWRIRGFlNps5F+PMSKYF/R2fQ8wq9jxu\nuwolKRk3p9l/b85RinWcoxTrzGYzGhoaDJ9vKJ3jtttuQ2ZmJhobG3Hy5EnU19cjJSUFjY2NGB4e\nxooVK7B27VqvY0RE0SKycyF9lblz2Fmdg4iIdDNc4m7z5s0e/966davnhU0mr2NERFFjyfNdocPB\njYVERKQfm60QUWKw5AA2f0E0S9wREZE+DKKJKCFo6RyeQbQcGgKGhrTKHURERDowiCaixGDJ9U7n\ncNiB9AwIIaIzJiIimrYYRBNRYrDkAHYbpDoydszJVA4iIjKGQTQRJQRhSgLS0gH79bGDbLRCREQG\nMYgmosRhyfXYXCgddoh0rkQTEZF+DKKJKHFkewbRWjoHV6KJiEg/BtFElDBEdh7k+M2FTOcgIiKD\nGEQTUeKw5HhW6GCjFSIiMohBNBElDq+c6F4IVucgIiIDGEQTUcLwarjitAPpXIkmIiL9GEQTUeKw\n5Hmmc/QynYOIiIxhEE1EiSPTAjjskCOuhitstkJERAYxiCaihCFMJi1otl+DHB4GBgeA1PRoD4uI\niKYhU7QHQEQUUZZcLaVDmQGkpkMoXEsgIiL9GEQTUWJxbS4UM2cyH5qIiAxjEE1ECUWMlrlLz2AQ\nTUREhvFzTCJKLK50DumwQ6RzUyERERnDIJqIEoq7VjRbfhMRUQgYRBNRYrHkArarrvJ2DKKJiMgY\nBtFElFhGq3M4GEQTEZFxDKKJKLFkWQBnL+T1axBstEJERAYxiCaihCKUGUBmFvDF77kSTUREhjGI\nJqLEY8kFrnUD6QyiiYjIGAbRRJRwhCVX+4LpHEREZBCDaCJKPNm5gBBAujnaIyEiommKQTQRJR5L\nLpCWruVHExERGcAgmogSjsjOZT40ERGFhEE0ESWe0gqIpSujPQoiIprGTNEeABFRpIncfIj7H472\nMIiIaBrjSjQRERERkU4MoomIiIiIdGIQTURERESkE4NoIiIiIiKdGEQTEREREenEIJqIiIiISCfD\nJe6am5vR0dGBRx99FDt27IDNZkN+fj62bNmC4eFhr2NERERERPHC0Eq01WrFJ598AgDYv38/iouL\nsX37dlitVhw6dMjnMSIiIiKieGEoiH799dexadMmAMDp06excuVKtLW1obKyEidOnPA61traGtZB\nExERERFFk+4geu/evaitrYXFYgEAOBwOpKWloaWlBfX19ejt7fU6Zrfbwz5wIiIiIqJo0Z0T/ckn\nn2BwcBD79u1DT08PSkpKsHv3btTX18NmsyEzMxPJyckex7KysqZi7EREREREUaE7iH7yyScBAD09\nPWhqasLChQtx+PBhlJWVYefOnViyZAmcTqfXMV9OnTqFU6dOuf/d0NCAoqIigz8KUXiZzeZoD4Eo\nIM5RinWcoxTrmpqa3F9XV1ejuro66HMNl7iTUgIA1q5di5SUFDQ2NmJ4eBgrVqzwecyX6upqNDQ0\nuP8XSeNftGjiODzFyji2bdsW7SHEzGvBcXiKlXFwjo7hODzFyjhiYY4CsfF6xMIYAI5jom3btnnE\noXoCaCCEEnd5eXnu0nVbt271vKjJ5HUs1uh9oaYKx+EpVsaRl5cX7SHEzGvBcXiKlXFwjo7hODzF\nyjhiYY4CsfF6xMIYAI5jolDnqJCjS8pE5NbU1BTxT0eI9OAcpVjHOUqxLtQ5yo6FRD7EyrtkIn84\nRynWcY5SrAt1jnIlmoiIiIhIJ65EExERERHpxCCaiIiIiEgnw9U5iKarffv24ZVXXsGLL76I9PR0\nvPbaa2hvb0dycjK+973vwW63Y+fOnRgYGMDcuXPx8MMPo62tDT/5yU8wa9YsAMBDDz2E8vLyKP8k\nFK/Gz9HBwUGv+Wi1WvHiiy9CSomRkRH84Ac/gMlkwo4dO2Cz2ZCfn++unkQ0FSabo6Oam5vR0dGB\nLVu28D5KETfZPD1+/Dh2794NAO7jjzzySND30hnPPPPMMxH6WYii7sKFC+ju7saNGzewZs0aDAwM\n4Le//S2+//3v48yZM8jOzkZzczM2bNiABx54AAcOHIDFYoGqqkhPT8eWLVtQV1fnbntPFG4T5+iu\nXbu85mNBQQHq6uqwbt06XLx4EampqWhtbUVSUhIee+wxvP3220hLS0NxcXG0fxyKQ8HM0ZycHFit\nVjQ3NyM9PR3Lly9Hd3c376MUMcHM0+rqatTV1aGurg7Xr19HVVUVPv3006DvpUznoIQyd+5cfPWr\nX3X/OyMjAwMDA/jd734Hu92OsrIyDA4OAgCGh4fhcDhw+vRpJCUl4aOPPsKzzz6LgwcPRmv4lAAm\nzlFf8zElJQUmkwlDQ0P44osvMHfuXLS1tWHlypVoa2tDZWUlWltbo/UjUJwLZo4CwOuvv45Nmza5\nH8f7KEVSsPMUADo7O9He3o5ly5bpupcynYMSXmlpKZqbm1FdXQ1FUdDQ0IBXX30VAFBRUQGHw4HK\nyko8//zzsNvt+NGPfoSCggLMmTMnyiOnROBrPo567bXX8OCDD2LmzJlwOp1IS0vDnj17sGHDBuza\ntStaQ6YE42uO7t27F7W1tR6rzbyPUjQFupf+4he/wKOPPgoAuu6lDKIpoR07dgwA0NjYiBdeeAHH\njx/HkiVL8NRTTwEA3n33XYyvApmZmYk77rgDZ8+e5c2fIqKoqMjnfHzrrbdQW1uL+fPnAwDMZjOa\nm5tRX18Pm82GrKysqI2ZEouvOXr06FEMDAxg37596OnpwUsvvYTNmzcD4H2UosPfvfTgwYNYsGAB\ncnJyAOi7lzKdgxKWlBKXLl1CZmYmAG2V5NKlS1BVFQAwNDSE/fv3o7a2Fn19fe5fuDNnzqCkpCRq\n46bE4ms+dnR0oKOjA8uWLXM/rrq6Gl1dXSgrK8OHH36ImpqaaA2ZEoyvOfrEE09g27Zt2Lp1KxYv\nXozNmzfzPkpR5WueAsDhw4exatUq9+P03Eu5Ek0J5eLFi3jrrbfQ0dGBn/3sZ1i0aBGOHj2KI0eO\nwGQy4fHHH0d7eztefvllzJgxA+vXr0dRURFOnDiBN998EyaTCYsWLcLChQuj/aNQnBo/R3/605+i\nqqoKLS0tHvPxwIEDOH/+PLZv3w4AuO+++7B27VqcOHECjY2NKCwsxIoVK6L8k1C8CmaO+nL+/Hne\nRyligp2nNpsNZrPZfZ6eeyk7FhIRERER6cR0DiIiIiIinRhEExERERHpxCCaiIiIiEgnBtFERERE\nRDoxiCYiIiIi0olBNBERERGRTgyiiYiIiIh0YhBNRERERKTTfwP2jn63nyqVcgAAAABJRU5ErkJg\ngg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10df05860>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "nile = pydetect.datasets.get_nile()\n",
    "nile.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/sin/anaconda/envs/py35/lib/python3.5/site-packages/pydetect-0.1.0.dev0-py3.5.egg/pydetect/changepoint.py:22: RuntimeWarning: invalid value encountered in true_divide\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "1871-01-01    0.0\n",
       "1872-01-01    0.0\n",
       "1873-01-01    0.0\n",
       "1874-01-01    0.0\n",
       "             ... \n",
       "1967-01-01    0.0\n",
       "1968-01-01    0.0\n",
       "1969-01-01    0.0\n",
       "1970-01-01    0.0\n",
       "Freq: AS-JAN, dtype: float64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "detector = pydetect.MeanDetector()\n",
    "cpt = detector.detect(nile)\n",
    "cpt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x10e0525c0>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAswAAAEDCAYAAAAhh1LmAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAADggMAMAAAAOPgvLPF/t0hSFE4AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10ca256d8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cpt.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}
